code: def testNumericKerasInput(self):
      key = "feature_key"
      batch_size = 3
      state_dims = 5
      input_shape = (batch_size, state_dims)
      keras_input = tf.keras.Input(
          shape=[state_dims], dtype=tf.int32, name=key
      )
      state = {key: tf.ones(input_shape, tf.int32)}
      input_spec = {key: tensor_spec.TensorSpec([state_dims], tf.int32)}
  
      network = encoding_network.EncodingNetwork(
          input_spec,
          preprocessing_combiner=tf.keras.Sequential([keras_input]),
      )
  
      output, _ = network(state)
      self.assertEqual(input_shape, output.shape)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tf_agents.networks import encoding_network
  from tf_agents.specs import tensor_spec
  from tf_agents.utils import test_utils
label_desc: Use image node_id 13 for calling the EncodingNetworkTest obj's underlying member method code with example usage: obj.testNumericKerasInput() without return types